Mohamed Abdelfattah

Mohamed Abdelfattah is an Assistant Professor at Cornell Tech and the School of Electrical and Computer Engineering, Cornell University, specializing in machine-learning-centric computer systems for datacenters and mobile devices.

Education:

• B.S., Electrical and Computer Engineering, German University in Cairo (2009)
• M.S., Electrical and Computer Engineering, University of Stuttgart (2011)
• Ph.D., Electrical and Computer Engineering, University of Toronto (2016)

His research bridges computer architecture and machine learning with core focus areas:

• Deep learning systems optimization
• Hardware-aware automated machine learning
• Reconfigurable computing architectures
• FPGA-based acceleration

He pioneers hardware-software co-design approaches to enhance ML efficiency across computing platforms.

Awards:

• National Science Foundation Early CAREER Award (2024)
• Vanier Canada Graduate Scholarship
• Three best paper awards for embedded networks-on-chip for FPGAs

His research is funded by the NSF CAREER grant, building on industrial collaborations from prior roles at Intel's Programmable Solutions Group and Samsung where he led hardware-aware ML research teams. His PhD work on FPGA architectures has been adopted by multiple semiconductor companies.